def test_simple_level_4_recon_ext_mode_4():
# Test for perfect reconstruction with 3 levels
crop_ellipsoid = ellipsoid[:62,:54,:58]
Yl, Yh = dtwavexfm3(crop_ellipsoid, 4, ext_mode=4)
ellipsoid_recon = dtwaveifm3(Yl, Yh)
assert crop_ellipsoid.size == ellipsoid_recon.size
assert np.max(np.abs(crop_ellipsoid - ellipsoid_recon)) < TOLERANCE
def test_integer_perfect_recon():
# Check that an integer input is correctly coerced into a floating point
# array and reconstructed
A = (np.random.random((4,4,4)) * 5).astype(np.int32)
Yl, Yh = dtwavexfm3(A)
B = dtwaveifm3(Yl, Yh)
assert np.max(np.abs(A-B)) < 1e-12
def test_integer_perfect_recon():
# Check that an integer input is correctly coerced into a floating point
# array and reconstructed
A = (np.random.random((4, 4, 4)) * 5).astype(np.int32)
Yl, Yh = dtwavexfm3(A)
B = dtwaveifm3(Yl, Yh)
assert np.max(np.abs(A - B)) < 1e-12
def test_simple_level_4_recon_ext_mode_4():
# Test for perfect reconstruction with 3 levels
crop_ellipsoid = ellipsoid[:62, :54, :58]
Yl, Yh = dtwavexfm3(crop_ellipsoid, 4, ext_mode=4)
ellipsoid_recon = dtwaveifm3(Yl, Yh)
assert crop_ellipsoid.size == ellipsoid_recon.size
assert np.max(np.abs(crop_ellipsoid - ellipsoid_recon)) < TOLERANCE
def test_simple_level_4_recon_custom_wavelets():
# Test for perfect reconstruction with 3 levels
b = biort('legall')
q = qshift('qshift_06')
Yl, Yh = dtwavexfm3(ellipsoid, 4, biort=b, qshift=q)
ellipsoid_recon = dtwaveifm3(Yl, Yh, biort=b, qshift=q)
assert ellipsoid.size == ellipsoid_recon.size
assert np.max(np.abs(ellipsoid - ellipsoid_recon)) < TOLERANCE
def test_level_4_recon_discarding_level_1():
# Test for non-perfect but reasonable reconstruction
Yl, Yh = dtwavexfm3(ellipsoid, 4, discard_level_1=True)
ellipsoid_recon = dtwaveifm3(Yl, Yh)
assert ellipsoid.size == ellipsoid_recon.size
# Check that we mostly reconstruct correctly
assert np.median(np.abs(ellipsoid - ellipsoid_recon)[:]) < 1e-3
def test_float32_recon():
# Check that an float32 input is correctly output as float32
Yl, Yh = dtwavexfm3(ellipsoid.astype(np.float32))
assert np.issubsctype(Yl.dtype, np.float32)
assert np.all(list(np.issubsctype(x.dtype, np.complex64) for x in Yh))
recon = dtwaveifm3(Yl, Yh)
assert np.issubsctype(recon.dtype, np.float32)
def test_simple_level_4_recon_custom_wavelets():
# Test for perfect reconstruction with 3 levels
b = biort('legall')
q = qshift('qshift_06')
Yl, Yh = dtwavexfm3(ellipsoid, 4, biort=b, qshift=q)
ellipsoid_recon = dtwaveifm3(Yl, Yh, biort=b, qshift=q)
assert ellipsoid.size == ellipsoid_recon.size
assert np.max(np.abs(ellipsoid - ellipsoid_recon)) < TOLERANCE
def test_level_4_recon_discarding_level_1():
# Test for non-perfect but reasonable reconstruction
Yl, Yh = dtwavexfm3(ellipsoid, 4, discard_level_1=True)
ellipsoid_recon = dtwaveifm3(Yl, Yh)
assert ellipsoid.size == ellipsoid_recon.size
# Check that we mostly reconstruct correctly
assert np.median(np.abs(ellipsoid - ellipsoid_recon)[:]) < 1e-3
def test_float32_recon():
# Check that an float32 input is correctly output as float32
Yl, Yh = dtwavexfm3(ellipsoid.astype(np.float32))
assert np.issubsctype(Yl.dtype, np.float32)
assert np.all(list(np.issubsctype(x.dtype, np.complex64) for x in Yh))
recon = dtwaveifm3(Yl, Yh)
assert np.issubsctype(recon.dtype, np.float32)
def test_simple_level_1_recon_haar():
# Test for perfect reconstruction with 1 level and Haar wavelets
# Form Haar wavelets
h0 = np.array((1.0, 1.0))
g0 = h0
h0 = h0 / np.sum(h0)
g0 = g0 / np.sum(g0)
h1 = g0 * np.cumprod(-np.ones_like(g0))
g1 = -h0 * np.cumprod(-np.ones_like(h0))
haar = (h0, g0, h1, g1)
Yl, Yh = dtwavexfm3(ellipsoid, 1, biort=haar)
ellipsoid_recon = dtwaveifm3(Yl, Yh, biort=haar)
assert ellipsoid.size == ellipsoid_recon.size
assert np.max(np.abs(ellipsoid - ellipsoid_recon)) < TOLERANCE
def test_simple_level_1_recon_haar():
# Test for perfect reconstruction with 1 level and Haar wavelets
# Form Haar wavelets
h0 = np.array((1.0, 1.0))
g0 = h0
h0 = h0 / np.sum(h0)
g0 = g0 / np.sum(g0)
h1 = g0 * np.cumprod(-np.ones_like(g0))
g1 = -h0 * np.cumprod(-np.ones_like(h0))
haar = (h0, g0, h1, g1)
Yl, Yh = dtwavexfm3(ellipsoid, 1, biort=haar)
ellipsoid_recon = dtwaveifm3(Yl, Yh, biort=haar)
assert ellipsoid.size == ellipsoid_recon.size
assert np.max(np.abs(ellipsoid - ellipsoid_recon)) < TOLERANCE
def test_simple_level_4_recon():
# Test for perfect reconstruction with 3 levels
Yl, Yh = dtwavexfm3(ellipsoid, 4)
ellipsoid_recon = dtwaveifm3(Yl, Yh)
assert ellipsoid.size == ellipsoid_recon.size
assert np.max(np.abs(ellipsoid - ellipsoid_recon)) < TOLERANCE
def test_simple_level_4_recon():
# Test for perfect reconstruction with 3 levels
Yl, Yh = dtwavexfm3(ellipsoid, 4)
ellipsoid_recon = dtwaveifm3(Yl, Yh)
assert ellipsoid.size == ellipsoid_recon.size
assert np.max(np.abs(ellipsoid - ellipsoid_recon)) < TOLERANCE
